Agri-footprint 8: will your results change?

Shifts across the database

To quantify the impact of these changes on the database as a whole, we calculated all impacts before and after each of the updates. The result gives a clear overview of the changes in impacts.

Most datasets sit close to 0%, while a smaller group shifts by more than 50% in either direction. Including land use change and peat, the median change is around 9%; excluding them, it is around 1%. When we look at the global warming excluding the land use change and peat oxidation the impacts are less variable.

When we look at these changes in isolation, we can trace how specific changes affected the impacts over specific groups.

For the land occupation and NPK updates, the median change is close to zero (0–1%). Individual crops may shift up or down, but there is no systematic shift towards higher or lower emissions across the database.

With the peat update, Agri-footprint 8 captures emissions from drained peat soils more completely, based on the latest National Inventory Reports. As a result, impacts are higher for crops grown in regions with peat soils. 

_{Figure 1 - Change in climate impact per dataset, Agri-footprint 7 vs 8. distribution of the change. Use the toggle above to see the switch between impact categories.} 

Example: rice from Thailand

In Agri-footprint 8, we updated the rice methane modelling for PEF compliancy. Under flooded conditions, organic matter decomposes anaerobically, producing methane that is released into the atmosphere throughout the cultivation cycle. By accounting for these organic residues along with ecosystem-specific water regimes, regional cultivation lengths, and farm-level inputs like straw and manure, Agri-footprint 8 provides a more accurate reflection of paddy emissions. 

As illustrated in figure 2, in Thai paddy rice cultivation, these methodological updates contribute to an overall increase in global warming potential compared to version 7.

_{Figure 2 – What drives the change? Contribution of each update to the climate impact of rice from Thailand (incl. LUC and peat, kg CO₂-eq/kg), from Agri-footprint 7 (top bar) to Agri-footprint 8 (bottom bar).}

_{Figure 3 – What drives the change? Contribution of each update to the climate impact of refined sunflower oil from Argentina (incl. LUC and peat, kg CO₂-eq/kg), from Agri-footprint 7 (top bar) to Agri-footprint 8 (bottom bar).}

Example 2: refined sunflower oil from Argentina 

The increased footprint for Argentine refined sunflower oil was primarily driven by updated peat modeling, which now applies a hierarchical data framework combining National Inventory Reports (NIR, 2022) with cropland maps from Cao et al. (2026) for a more comprehensive account of drained peatland emissions.

On the other hand, the primary driver for emission reductions was our updated country-specific wet climate factor (Frac). By better tailoring indirect N₂O modeling to local moisture regimes, this refinement substantially reduces calculated indirect N₂O emissions across drier agricultural regions such as Argentina.

Credibility of Agri-footprint

Built on transparency and independent review

Agri-footprint version 8 represents our largest update since its initial release in 2013. While credibility is built over years with transparency and decades of pioneering experience, we also commissioned an external review.

To ensure methodological compliance, Agri-footprint 8 was critically reviewed by Agroscope, Switzerland’s federal centre of excellence for agricultural research. Applying ISO 14044 criteria adapted for a background database, Dr. Thomas Nemecek and his team conducted an in-depth audit of our data and methodology.

What further distinguishes Agri-footprint is our approach to change traceability. We believe that by isolating the updates, we can identify and explain the specific drivers behind changes in environmental impact results, providing users with transparency and confidence in the data.